Search

Your search keyword '"Scott, Russell"' showing total 2,252 results
Start Over Author "Scott, Russell"

Refine your results

more »

more »

more »

more »

more »

more »

more »
2,252 results on '"Scott, Russell"'

1. Cover

Author

Grose, David Frederick and Scott, Russell

Published
2017

10. Preface

Author

Grose, David Frederick and Scott, Russell

Published
2017

11. 4. The Catalogue

Author

Grose, David Frederick and Scott, Russell

Published
2017

14. List of Plates

Author

Grose, David Frederick and Scott, Russell

Published
2017

15. Abbreviations

Author

Grose, David Frederick and Scott, Russell

Published
2017

19. Exceptional heat and atmospheric dryness amplified losses of primary production during the 2020 U.S. Southwest hot drought

Author

Dannenberg, Matthew P, Yan, Dong, Barnes, Mallory L, Smith, William K, Johnston, Miriam R, Scott, Russell L, Biederman, Joel A, Knowles, John F, Wang, Xian, Duman, Tomer, Litvak, Marcy E, Kimball, John S, Williams, A Park, and Zhang, Yao

Subjects
Carbon Cycle, Droughts, Ecosystem, Hot Temperature, Soil, drought, drylands, gross primary production, soil moisture, vapor pressure deficit, warming, Environmental Sciences, Biological Sciences, Ecology
Abstract

Earth's ecosystems are increasingly threatened by "hot drought," which occurs when hot air temperatures coincide with precipitation deficits, intensifying the hydrological, physiological, and ecological effects of drought by enhancing evaporative losses of soil moisture (SM) and increasing plant stress due to higher vapor pressure deficit (VPD). Drought-induced reductions in gross primary production (GPP) exert a major influence on the terrestrial carbon sink, but the extent to which hotter and atmospherically drier conditions will amplify the effects of precipitation deficits on Earth's carbon cycle remains largely unknown. During summer and autumn 2020, the U.S. Southwest experienced one of the most intense hot droughts on record, with record-low precipitation and record-high air temperature and VPD across the region. Here, we use this natural experiment to evaluate the effects of hot drought on GPP and further decompose those negative GPP anomalies into their constituent meteorological and hydrological drivers. We found a 122 Tg C (>25%) reduction in GPP below the 2015-2019 mean, by far the lowest regional GPP over the Soil Moisture Active Passive satellite record. Roughly half of the estimated GPP loss was attributable to low SM (likely a combination of record-low precipitation and warming-enhanced evaporative depletion), but record-breaking VPD amplified the reduction of GPP, contributing roughly 40% of the GPP anomaly. Both air temperature and VPD are very likely to continue increasing over the next century, likely leading to more frequent and intense hot droughts and substantially enhancing drought-induced GPP reductions.

Published
2022

22. Confronting the water potential information gap

Author

Novick, Kimberly A, Ficklin, Darren L, Baldocchi, Dennis, Davis, Kenneth J, Ghezzehei, Teamrat A, Konings, Alexandra G, MacBean, Natasha, Raoult, Nina, Scott, Russell L, Shi, Yuning, Sulman, Benjamin N, and Wood, Jeffrey D

Subjects
Earth Sciences, Physical Geography and Environmental Geoscience, Meteorology & Atmospheric Sciences, Physical geography and environmental geoscience
Abstract

Water potential directly controls the function of leaves, roots, and microbes, and gradients in water potential drive water flows throughout the soil-plant-atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in-situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely-sensed proxies. Together, these considerations offer a roadmap for clearer links between ecohydrological processes and the water potential gradients that have the 'potential' to substantially reduce conceptual and modeling uncertainties.

Published
2022

23. The three major axes of terrestrial ecosystem function

Author

Migliavacca, Mirco, Musavi, Talie, Mahecha, Miguel D, Nelson, Jacob A, Knauer, Jürgen, Baldocchi, Dennis D, Perez-Priego, Oscar, Christiansen, Rune, Peters, Jonas, Anderson, Karen, Bahn, Michael, Black, T Andrew, Blanken, Peter D, Bonal, Damien, Buchmann, Nina, Caldararu, Silvia, Carrara, Arnaud, Carvalhais, Nuno, Cescatti, Alessandro, Chen, Jiquan, Cleverly, Jamie, Cremonese, Edoardo, Desai, Ankur R, El-Madany, Tarek S, Farella, Martha M, Fernández-Martínez, Marcos, Filippa, Gianluca, Forkel, Matthias, Galvagno, Marta, Gomarasca, Ulisse, Gough, Christopher M, Göckede, Mathias, Ibrom, Andreas, Ikawa, Hiroki, Janssens, Ivan A, Jung, Martin, Kattge, Jens, Keenan, Trevor F, Knohl, Alexander, Kobayashi, Hideki, Kraemer, Guido, Law, Beverly E, Liddell, Michael J, Ma, Xuanlong, Mammarella, Ivan, Martini, David, Macfarlane, Craig, Matteucci, Giorgio, Montagnani, Leonardo, Pabon-Moreno, Daniel E, Panigada, Cinzia, Papale, Dario, Pendall, Elise, Penuelas, Josep, Phillips, Richard P, Reich, Peter B, Rossini, Micol, Rotenberg, Eyal, Scott, Russell L, Stahl, Clement, Weber, Ulrich, Wohlfahrt, Georg, Wolf, Sebastian, Wright, Ian J, Yakir, Dan, Zaehle, Sönke, and Reichstein, Markus

Subjects
Life on Land, Carbon Cycle, Carbon Dioxide, Climate, Datasets as Topic, Ecosystem, Humidity, Plants, Principal Component Analysis, Water Cycle, General Science & Technology
Abstract

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Published
2021

24. Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions

Author

Helbig, Manuel, Gerken, Tobias, Beamesderfer, Eric R, Baldocchi, Dennis D, Banerjee, Tirtha, Biraud, Sébastien C, Brown, William OJ, Brunsell, Nathaniel A, Burakowski, Elizabeth A, Burns, Sean P, Butterworth, Brian J, Chan, W Stephen, Davis, Kenneth J, Desai, Ankur R, Fuentes, Jose D, Hollinger, David Y, Kljun, Natascha, Mauder, Matthias, Novick, Kimberly A, Perkins, John M, Rahn, David A, Rey-Sanchez, Camilo, Santanello, Joseph A, Scott, Russell L, Seyednasrollah, Bijan, Stoy, Paul C, Sullivan, Ryan C, de Arellano, Jordi Vilà-Guerau, Wharton, Sonia, Yi, Chuixiang, and Richardson, Andrew D

Subjects
Earth Sciences, Atmospheric Sciences, Eddy covariance, Boundary layer, Land-atmosphere, Remote sensing, Atmospheric inversion models, Biological Sciences, Agricultural and Veterinary Sciences, Meteorology & Atmospheric Sciences, Agricultural, veterinary and food sciences, Biological sciences, Earth sciences
Abstract

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous and mountainous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

Published
2021

25. A randomized phase 2b trial examined the effects of the glucagon-like peptide-1 and glucagon receptor agonist cotadutide on kidney outcomes in patients with diabetic kidney disease

Author

Selvarajah, Viknesh, Robertson, Darren, Hansen, Lars, Jermutus, Lutz, Smith, Kirsten, Coggi, Angela, Sánchez, José, Chang, Yi-Ting, Yu, Hongtao, Parkinson, Joanna, Khan, Anis, Chung, H. Sophia, Hess, Sonja, Dumas, Richard, Duck, Tabbatha, Jolly, Simran, Elliott, Tom G., Baker, John, Lecube, Albert, Derwahl, Karl-Michael, Scott, Russell, Morales, Cristobal, Peters, Carl, Goldenberg, Ronald, Parker, Victoria E.R., and Heerspink, Hiddo J.L.

Published
2024
Full Text
View/download PDF

26. Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Author

Chu, Housen, Luo, Xiangzhong, Ouyang, Zutao, Chan, W Stephen, Dengel, Sigrid, Biraud, Sébastien C, Torn, Margaret S, Metzger, Stefan, Kumar, Jitendra, Arain, M Altaf, Arkebauer, Tim J, Baldocchi, Dennis, Bernacchi, Carl, Billesbach, Dave, Black, T Andrew, Blanken, Peter D, Bohrer, Gil, Bracho, Rosvel, Brown, Shannon, Brunsell, Nathaniel A, Chen, Jiquan, Chen, Xingyuan, Clark, Kenneth, Desai, Ankur R, Duman, Tomer, Durden, David, Fares, Silvano, Forbrich, Inke, Gamon, John A, Gough, Christopher M, Griffis, Timothy, Helbig, Manuel, Hollinger, David, Humphreys, Elyn, Ikawa, Hiroki, Iwata, Hiroki, Ju, Yang, Knowles, John F, Knox, Sara H, Kobayashi, Hideki, Kolb, Thomas, Law, Beverly, Lee, Xuhui, Litvak, Marcy, Liu, Heping, Munger, J William, Noormets, Asko, Novick, Kim, Oberbauer, Steven F, Oechel, Walter, Oikawa, Patty, Papuga, Shirley A, Pendall, Elise, Prajapati, Prajaya, Prueger, John, Quinton, William L, Richardson, Andrew D, Russell, Eric S, Scott, Russell L, Starr, Gregory, Staebler, Ralf, Stoy, Paul C, Stuart-Haëntjens, Ellen, Sonnentag, Oliver, Sullivan, Ryan C, Suyker, Andy, Ueyama, Masahito, Vargas, Rodrigo, Wood, Jeffrey D, and Zona, Donatella

Subjects
Earth Sciences, Flux footprint, Spatial representativeness, Landsat EVI, Land cover, Sensor location bias, Model-data benchmarking, Biological Sciences, Agricultural and Veterinary Sciences, Meteorology & Atmospheric Sciences, Agricultural, veterinary and food sciences, Biological sciences, Earth sciences
Abstract

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Published
2021

28. COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Author

Bond‐Lamberty, Ben, Christianson, Danielle S, Malhotra, Avni, Pennington, Stephanie C, Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Arain, M Altaf, Armesto, Juan J, Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Black, Thomas Andrew, Buchmann, Nina, Carbone, Mariah S, Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S, Davidson, Eric A, Desai, Ankur R, Drake, John E, El‐Madany, Tarek S, Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M, Goulden, Michael, Gregg, Jillian, del Arroyo, Omar Gutiérrez, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A, Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A, McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F, Nietz, Jennifer G, Nilsson, Mats B, Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S, Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F, Phillips, Claire L, Phillips, Richard P, Raich, James W, Renchon, Alexandre A, Ruehr, Nadine K, Sánchez‐Cañete, Enrique P, Saunders, Matthew, Savage, Kathleen E, Schrumpf, Marion, Scott, Russell L, Seibt, Ulli, Silver, Whendee L, Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G, Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K, Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E, Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang

Subjects
Climate Change Impacts and Adaptation, Environmental Sciences, Climate Action, Atmosphere, Carbon Dioxide, Ecosystem, Greenhouse Gases, Methane, Nitrous Oxide, Reproducibility of Results, Respiration, Soil, carbon dioxide, greenhouse gases, methane, open data, open science, soil respiration, Biological Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Published
2020

32. Kidney and Cardiovascular Effects of Canagliflozin According to Age and Sex: A Post Hoc Analysis of the CREDENCE Randomized Clinical Trial

Author

Perkovic, Vlado, Mahaffey, Kenneth W., Agarwal, Rajiv, Bakris, George, Brenner, Barry M., Cannon, Christopher P., Charytan, David M., de Zeeuw, Dick, Greene, Tom, Jardine, Meg J., Heerspink, Hiddo J.L., Levin, Adeera, Meininger, Gary, Neal, Bruce, Pollock, Carol, Wheeler, David C., Zhang, Hong, Zinman, Bernard, Jardine, Meg, Li, Nicole, Kolesnyk, Inna, Aizenberg, Diego, Pecoits-Filho, Roberto, Cherney, David, Obrador, Gregorio, Chertow, Glenn, Chang, Tara, Hawley, Carmel, Ji, Linong, Wada, Takashi, Jha, Vivekanand, Lim, Soo Kun, Lim-Abrahan, Mary Anne, Santos, Florence, Chae, Dong-Wan, Hwang, Shang-Jyh, Vazelov, Evgueniy, Rychlík, Ivan, Hadjadj, Samy, Krane, Vera, Rosivall, László, De Nicola, Luca, Dreval, Alexander, Nowicki, Michał, Schiller, Adalbert, Distiller, Larry, Górriz, Jose L., Kolesnyk, Mykola, David, Wheeler, C., Guerrero, Rodolfo Andres Ahuad, Albisu, Juan Pablo, Alvarisqueta, Andres, Bartolacci, Ines, Berli, Mario Alberto, Bordonava, Anselmo, Calella, Pedro, Cantero, Maria Cecilia, Cartasegna, Luis Rodolfo, Cercos, Esteban, Coloma, Gabriela Cecilia, Colombo, Hugo, Commendatore, Victor, Cuadrado, Jesus, Cuneo, Carlos Alberto, Cusumano, Ana Maria, Douthat, Walter Guillermo, Dran, Ricardo Dario, Farias, Eduardo, Fernandez, Maria Florencia, Finkelstein, Hernan, Fragale, Guillermo, Fretes, Jose Osvaldo, Garcia, Nestor Horacio, Gastaldi, Anibal, Gelersztein, Elizabeth, Glenny, Jorge Archibaldo, Gonzalez, Joaquin Pablo, Colaso, Patricia del Carmen Gonzalez, Goycoa, Claudia, Greloni, Gustavo Cristian, Guinsburg, Adrian, Hermida, Sonia, Juncos, Luis Isaias, Klyver, Maria Isabel, Kraft, Florencia, Krynski, Fernando, Lanchiotti, Paulina Virginia, Leon de la Fuente, Ricardo Alfonso, Marchetta, Nora, Mele, Pablo, Nicolai, Silvia, Novoa, Pablo Antonio, Orio, Silvia Ines, Otreras, Fabian, Oviedo, Alejandra, Raffaele, Pablo, Resk, Jorge Hector, Rista, Lucas, Papini, Nelson Rodriguez, Sala, Jorgelina, Santos, Juan Carlos, Schiavi, Lilia Beatriz, Sessa, Horacio, Casabella, Tomas Smith, Ulla, Maria Rosa, Valdez, Maria, Vallejos, Augusto, Villarino, Adriana, Visco, Virginia Esther, Wassermann, Alfredo, Zaidman, Cesar Javier, Cheung, Ngai Wah, Droste, Carolyn, Fraser, Ian, Johnson, David, Mah, Peak Mann, Nicholls, Kathy, Packham, David, Proietto, Joseph, Roberts, Anthony, Roger, Simon, Tsang, Venessa, Raduan, Roberto Abrão, Costa, Fernando Augusto Alves da, Amodeo, Celso, Turatti, Luiz Alberto Andreotti, Bregman, Rachel, Sanches, Fernanda Cristina Camelo, Canani, Luis Henrique, Chacra, Antônio Roberto, Borges, João Lindolfo Cunha, Vêncio, Sérgio Alberto Cunha, Franco, Roberto Jorge da Silva, d’Avila, Domingos, Portes, Evandro de Souza, de Souza, Pedro, Deboni, Luciane Mônica, Fraige Filho, Fadlo, Neto, Bruno Geloneze, Gomes, Marcus, Kohara, Suely Keiko, Keitel, Elizete, Saraiva, Jose Francisco Kerr, Lisboa, Hugo Roberto Kurtz, Contieri, Fabiana Loss de Carvalho, Milagres, Rosângela, Junior, Renan Montenegro, de Brito, Claudia Moreira, Hissa, Miguel Nasser, Sabbag, Ângela Regina Nazario, Noronha, Irene, Panarotto, Daniel, Filho, Roberto Pecoits, Pereira, Márcio Antônio, Saporito, Wladmir, Scotton, Antonio Scafuto, Schuch, Tiago, de Almeida, Roberto Simões, Ramos, Cássio Slompo, Felício, João Soares, Thomé, Fernando, Hachmann, Jean Carlo Tibes, Yamada, Sérgio, Hayashida, Cesar Yoiti, Petry, Tarissa Beatrice Zanata, Zanella, Maria Teresa, Andreeva, Viktoria, Angelova, Angelina, Dimitrov, Stefan, Genadieva, Veselka, Genova-Hristova, Gabriela, Hristozov, Kiril, Kamenov, Zdravko, Koundurdjiev, Atanas, Lozanov, Lachezar, Margaritov, Viktor, Nonchev, Boyan, Rangelov, Rangel, Shinkov, Alexander, Temelkova, Margarita, Velichkova, Ekaterina, Yakov, Andrian, Aggarwal, Naresh, Aronson, Ronnie, Bajaj, Harpreet, Chouinard, Guy, Conway, James, Cournoyer, Serge, DaRoza, Gerald, De Serres, Sacha, Dubé, François, Goldenberg, Ronald, Gupta, Anil, Gupta, Milan, Henein, Sam, Khandwala, Hasnain, Leiter, Lawrence, Madore, François, McMahon, Alan, Muirhead, Norman, Pichette, Vincent, Rabasa-Lhoret, Remi, Steele, Andrew, Tangri, Navdeep, Torshizi, Ali, Woo, Vincent, Zalunardo, Nadia, Montenegro, María Alicia Fernández, Gonzalo Godoy Jorquera, Juan, Fariña, Marcelo Medina, Gajardo, Victor Saavedra, Vejar, Margarita, Chen, Nan, Chen, Qinkai, Gan, Shenglian, Kong, Yaozhong, Li, Detian, Li, Wenge, Li, Xuemei, Lin, Hongli, Liu, Jian, Lu, Weiping, Mao, Hong, Ren, Yan, Song, Weihong, Sun, Jiao, Sun, Lin, Tu, Ping, Wang, Guixia, Yang, Jinkui, Yin, Aiping, Yu, Xueqing, Zhao, Minghui, Zheng, Hongguang, Mendoza, Jose Luis Accini, Arcos, Edgar, Avendano, Jorge, Diaz Ruiz, Jorge Ernesto Andres, Ortiz, Luis Hernando Garcia, Gonzalez, Alexander, Triana, Eric Hernandez, Higuera, Juan Diego, Malaver, Natalia, de Salazar, Dora Inés Molina, Rosero, Ricardo, Alexandra Terront Lozano, Monica, Cometa, Luis Valderrama, Valenzuela, Alex, Vargas Alonso, Ruben Dario, Villegas, Ivan, Yupanqui, Hernan, Bartaskova, Dagmar, Barton, Petr, Belobradkova, Jana, Dohnalova, Lenka, Drasnar, Tomas, Ferkl, Richard, Halciakova, Katarina, Klokocnikova, Vera, Kovar, Richard, Lastuvka, Jiri, Lukac, Martin, Pesickova, Satu, Peterka, Karel, Pumprla, Jiri, Rychlik, Ivan, Saudek, Frantisek, Tesar, Vladimir, Valis, Martin, Weiner, Pavel, Zemek, Stanislav, Alamartine, Eric, Borot, Sophie, Cariou, Bertrand, Dussol, Bertrand, Fauvel, Jean-Pierre, Gourdy, Pierre, Klein, Alexandre, Le Meur, Yannick, Penfornis, Alfred, Roussel, Ronan, Saulnier, Pierre-Jean, Thervet, Eric, Zaoui, Philippe, Burst, Volker, Faghih, Markus, Faulmann, Grit, Haller, Hermann, Jerwan-Keim, Reinhold, Maxeiner, Stephan, Paschen, Björn, Plassmann, Georg, Rose, Ludger, Gonzalez Orellana, Ronaldo Arturo, Haase, Franklin Paul, Moreira Diaz, Juan Pablo, Ramirez Roca, Luis Alberto, Sánchez Arenales, Jose Antonio, Sanchez Polo, José Vicente, Juarez, Erick Turcios, Csecsei, Gyongyi, Csiky, Botond, Danos, Peter, Deak, Laszlo, Dudas, Mihaly, Harcsa, Eleonora, Keltai, Katalin, Keresztesi, Sandor, Kiss, Krisztian, Konyves, Laszlo, Major, Lajos, Mileder, Margit, Molnar, Marta, Mucsi, Janos, Oroszlan, Tamas, Ory, Ivan, Paragh, Gyorgy, Peterfai, Eva, Petro, Gizella, Revesz, Katalin, Takacs, Robert, Vangel, Sandor, Vasas, Szilard, Zsom, Marianna, Abraham, Oomman, Bhushan, Raju Sree, Deepak, Dewan, Edwin, Fernando M., Gopalakrishnan, Natarajan, Gracious, Noble, Hansraj, Alva, Jain, Dinesh, Keshavamurthy, C.B., Khullar, Dinesh, Manisha, Sahay, Peringat, Jayameena, Prasad, Narayan, Satyanarayana, Rao K., Sreedhar, Reddy, Sreelatha, Melemadathil, Sudhakar, Bhimavarapu, Chandra Vyasam, Ramesh, Bonadonna, Riccardo, Castellino, Pietro, Ceriello, Antonio, Chiovato, Luca, De Cosmo, Salvatore, Derosa, Giuseppe, Di Carlo, Alberto, Di Cianni, Graziano, Frascà, Giovanni, Fuiano, Giorgio, Gambaro, Giovanni, Garibotto, Giacomo, Giorda, Carlo, Malberti, Fabio, Mandreoli, Marcora, Mannucci, Edoardo, Orsi, Emanuela, Piatti, Piermarco, Santoro, Domenico, Sasso, Ferdinando Carlo, Serviddio, Gaetano, Stella, Andrea, Trevisan, Roberto, Veronelli, Anna Maria, Zanoli, Luca, Akiyama, Hitoshi, Aoki, Hiromi, Asano, Akimichi, Iitsuka, Tadashi, Kajiyama, Shizuo, Kashine, Susumu, Kawada, Toshio, Kodera, Takamoto, Kono, Hiroshi, Koyama, Kazunori, Kumeda, Yasuro, Miyauchi, Shozo, Mizuyama, Kazuyuki, Niiya, Tetsuji, Oishi, Hiroko, Ota, Satoshi, Sakakibara, Terue, Takai, Masahiko, Tomonaga, Osamu, Tsujimoto, Mitsuru, Wakasugi, Masakiyo, Wakida, Yasushi, Watanabe, Takayuki, Yamada, Masayo, Yanagida, Kazuhiro, Yanase, Toshihiko, Yumita, Wataru, Gaupsiene, Egle, Kozloviene, Dalia, Navickas, Antanas, Urbanaviciene, Egle, Abdul Ghani, Rohana, Kadir, Khalid Abdul, Ali, Norsiah, Che Yusof, Mohd Daud, Gan, Chye Lee, Ismail, Mastura, Kong, Wei Yen, Lam, Swee Win, Lee, Li Yuan, Loh, Chek Loong, Manocha, Anita Bhajan, Ng, Kee Sing, Ahmad, Nik Nur Fatnoon Nik, Ratnasingam, Vanassa, Shudim, Saiful Shahrizal Bin, Vengadasalam, Paranthaman, Abraira Munoz, Luis David, Salazar, Melchor Alpizar, Cruz, Juan Baas, Soto, Mario Burgos, Ramos, Jose Chevaile, Wong, Alfredo Chew, Correa Rotter, Jose Ricardo, Escalante, Tonatiu Diaz, Enriquez Sosa, Favio Edmundo, Lozano, Fernando Flores, Flota Cervera, Luis Fernando, Baron, Paul Frenk, Ballesteros, Cecilia Garcia, Gomez Rangel, Jose David, Herrera Jimenez, Luis Enrique, Irizar Santana, Sergio Saul, Flores, Fernando Jimenez, Molina, Hugo Laviada, Luna Ceballos, Rosa Isela, del Campo Blanco, Belia Martin, Franco, Guadalupe Morales, Moreno Loza, Oscar Tarsicio, Rocha, Cynthia Mustieles, Vera, Gregorio Obrador, Castellanos, Ricardo Orozco, Calcaneo, Juan Peralta, Reyes Rosano, Miguel Angel, Pattzi, Hiromi Rodriguez, Guzman, Juan Rosas, Rucker Joerg, Isabel Erika, Saavedra Sanchez, Sandra Berenice, Sanchez Mijangos, Jose Hector, Sanson, Pablo Serrano, Tamayo y Orozco, Juan Alfredo, Chavez, Eloisa Tellez, Cepeda, Alejandro Valdes, Carrillo, Luis Venegas, Mesa, Juan Villagordoa, Escobedo, Rolando Zamarripa, Baker, John, Noonan, Paul, Scott, Russell, Walker, Robert, Watson, Edward, Williams, Michael, Young, Simon, Abejuela, Zaynab, Agra, Jeimeen, Aquitania, Grace, Caringal, Clodoaido, Comia, Rhea Severina, Santos, Lalaine Delos, Gomez, Olivert, Jimeno, Cecilia, Tan, Gerry, Tolentino, Marsha, Yao, Christy, Yap, Yvette Ethel, Lallaine Ygpuara, Ma. Dovie, Bijata-Bronisz, Renata, Hotlos, Lucyna, Januszewicz, Andrzej, Kaczmarek, Barbara, Kaminska, Anna, Lazuka, Lech, Madej, Andrzej, Mazur, Stanislaw, Mlodawska-Choluj, Dorota, Nowicki, Michal, Orlowska-Kowalik, Grazyna, Popenda, Grazyna, Rewerska, Barbara, Sowinski, Dariusz, Angelescu, Liliana Monica, Anghel, Veronica, Avram, Rodica-Ioana, Busegeanu, Mihaela-Magdalena, Cif, Adriana, Cosma, Dana, Crisan, Carmen, Demian, Luiza Despina, Ferariu, Ioana Emilia, Halmagyi, Ildiko, Hancu, Nicolae, Munteanu, Mircea, Negru, Doru, Onaca, Adriana Gabriela, Petrica, Ligia, Popa, Amorin Remus, Ranetti, Aurelian-Emil, Serafinceanu, Cristian, Toarba, Cristina, Agafyina, Alina, Barbarash, Olga, Barysheva, Olga, Chizhov, Daniil, Dobronravov, Vladimir, Glinkina, Irina, Grineva, Elena, Khirmanov, Vladimir, Kolmakova, Elena, Koroleva, Tatiana, Kvitkova, Liudmila, Marasaev, Viacheslav, Mkrtumyan, Ashot, Morugova, Tatiana, Nagibovich, Galina, Nagibovich, Oleg, Nedogoda, Sergei, Osipova, Irina, Raskina, Tatiana, Samoylova, Yulia, Sazonova, Olga, Shamkhalova, Minara, Shutemova, Elena, Shwartz, Yuriy, Uriasyev, Oleg, Vorobyev, Sergey, Zateyshchikova, Anna, Zateyshshikov, Dmitry, Zykova, Tatyana, Antic, Slobodan, Djordjevic, Miodrag, Kendereski, Aleksandra, Lalic, Katarina, Lalic, Nebojsa, Popovic-Radinovic, Vesna, Babikova, Jana, Benusova, Olga, Buganova, Ingrid, Culak, Jan, Dzupina, Andrej, Dzuponova, Jana, Fulop, Peter, Ilavska, Adriana, Martinka, Emil, Ochodnicka, Zuzana, Pella, Daniel, Smatanova, Iveta, Ahmed, Fayzal, Badat, Aysha, Breedt, Johannes, Distiller, Lawrence, Govender, Vimladhevi, Govender, Ravendran, Joshi, Mukesh, Jurgens, Jaco, Latiff, Gulam, Lombard, Landman, Mookadam, Mohamed, Ngcakani, Nomangesi, Nortje, Hendrik, Oosthuizen, Helena, Pillay-Ramaya, Larisha, Prozesky, Hans, Reddy, Jeevren, Rheeder, Paul, Seeber, Mary, Cho, Young Min, Jeong, In-Kyung, Kim, Sin Gon, Kim, Yeong Hoon, Kwon, Hyuk-Sang, Kwon, Min Jeong, Lee, Byung-Wan, Lee, JungEun, Lee, Moon-Kyu, Nam, Moon-Suk, Oh, Kook-Hwan, Park, Cheol- Young, Park, Sun-Hee, Yoon, Kun Ho, Garcia, Pere Alvarez, Mercadal, Luis Asmarats, Barrios, Clara, Castro, Fernando Cereto, Guldris, Secundino Cigarran, Lopez, Marta Dominguez, Egido de los Rios, Jesus, Fresnedo, Gema Fernandez, Serrano, Antonio Galan, Garcia, Isabel, Gonzalez Martinez, Francisco Javier, Jodar Gimeno, Jose Esteban, Mendoza, Manuel Lopez, Marin, Tamara Malek, Portillo, Cristobal Morales, Munar Vila, Maria Antonia, Torres, Manuel Muñoz, Iglesias, Javier Nieto, Perez, Jonay Pantoja, Vera, Merce Perez, Portoles Perez, Jose M., Quesada Simón, María Angustias, Canonge, Rafael Simo, Gonzalez, Alfonso Soto, Riera, Manel Terns, Tinahones Madueno, Francisco Jose, Plaza, Mercedes Velo, Chang, Chwen-Tzuei, Chuang, Lee-Ming, Hsia, Te-Lin, Hsieh, Chang-Hsun, Lin, Chih-Ching, Lu, Yung- Chuan, Sheu, Wayne H-H, Barna, Olga, Bilyk, Svitlana D., Botsyurko, Volodymyr, Dudar, Iryna, Fushtey, Ivan, Godlevska, Olga, Golovchenko, Oleksandr, Gyrina, Olga, Kazmirchuk, Anatoliy, Komisarenko, Iuliia, Korzh, Oleksii, Kravchun, Nonna, Legun, Oleg, Mankovskyy, Borys, Martynyuk, Liliya, Mostovoy, Yuriy, Pashkovska, Nataliia, Pererva, Larysa, Pertseva, Tetyana, Samoylov, Oleksandr, Smirnov, Ivan, Svyshchenko, Yevgeniya, Tomashkevych, Halyna, Topchii, Ivan, Tryshchuk, Nadiya, Tseluyko, Vira, Vizir, Vadym, Vlasenko, Maryna, Zlova, Tetiana, Zub, Liliia, Abusnana, Salah, Railey, Mohamed, Abouglila, Kamal, Ainsworth, Paul, Ali, Zishan, Arutchelvam, Vijayaraman, Barnard, Maria, Bellary, Srikanth, Davies, Emyr, Davies, Mark, Davies, Simon, Dawson, Alison, El Kossi, Mohsen, English, Patrick, Fraser, Donald, Gnudi, Luigi, Gunstone, Anthony, Hall, Timothy, Hanif, Wasim, Jackson, Alan, Johnson, Andrew, Joseph, Franklin, Krishnan, Singhan, Kumwenda, Mick, MacDougall, Iain, Nixon, Paul, O'Hare, Joseph, Philip, Sam, Ramtoola, Shenaz, Saxena, Manish, Sennik, Davesh, Simon, Godwin, Singh, Baldev, Stephens, Jeffrey, Strzelecka, Anna, Symonds, Rehan, Turner, Wayne, Wahba, Mona, Wakeling, John, Wheeler, David, Winocour, Peter, Abdallah, Joseph, Abdullah, Raied, Abramowitz, Matthew, Acosta, Idalia, Aiello, Joseph, Akright, Laura, Akyea-Djamson, Ayim, Alappan, Rajendran, Alicic, Radica, Al-Karadsheh, Amer, Allison, Dale Crawford, Arauz-Pacheco, Carlos, Arfeen, Shahabul, Arif, Ahmed, Arvind, Moogali, Atray, Naveen, Awad, Ahmed, Barnhill, Peggy, Barranco, Elizabeth, Barrera, Carlos, Beacom, Matthew, Behara, Venkata, Belo, Diogo, Bentley-Lewis, Rhonda, Berenguer, Ramon, Bermudez, Lidia, Bernardo, Marializa, Biscoveanu, Mihaela, Bowman-Stroud, Cynthia, Brandon, Donald, Brusco, Osvaldo, Busch, Robert, Canaan, Yamil, Chilito, Alicia, Christensen, Tom, Christiano, Cynthia, Christofides, Elena, Chuateco, Caroucel, Cohen, Kenneth, Cohen, Robert, Cohen-Stein, Debbie, Cook, Charles, Coyne, Daniel, Daboul, Nizar, Darwish, Riad, Daswani, Adarsh, Deck, Kenneth, Desouza, Cyrus, Dev, Devasmita, Dhillon, Monika, Dua, Sohan, Eder, Frank, Elosegui, Ana Maria, El-Shahawy, Mohamed, Ervin, John, Esquenazi, Alberto, Evans, John, Fishbane, Steven, Frias, Juan, Galindo-Ramos, Eugenia, Galphin, Claude, Ghazi, Adline, Gonzalez, Enrique, Gorson, David, Gowda, Anupama, Greco, Barbara, Grubb, Stephen, Gulati, Rakesh, Hammoud, Jamal, Handelsman, Stuart, Hartman, Israel, Hershon, Kenneth, Hiser, Daniel, Hon, George, Jacob, Radu, Jaime, Maria, Jamal, Aamir, Kaupke, Charles, Keightley, Gerald, Kern, Elizabeth, Khanna, Rakhi, Khitan, Zeid, Kim, Sun, Kopyt, Nelson, Kovesdy, Csaba, Krishna, Gopal, Kropp, Jeffrey (Jay), Kumar, Amrendra, Kumar, Jayant, Kumar, Neil, Kusnir, Jorge, Lane, Wendy, Lawrence, Mary, Lehrner, Lawrence, Lentz, John, Levinson, Dennis, Lewis, Derek, Liss, Kenneth, Maddux, Andreas, Maheshwari, Hiralal, Mandayam, Sreedhar, Marar, Isam, Mehta, Bhasker, Middleton, John, Mordujovich, Jorge, Moreda, Ramon, Moustafa, Moustafa, Trenche, Samuel Mujica, Narayanan, Mohanram, Narvarte, Javier, Nassar, Tareq, Newman, George, Nichol, Brian, Nicol, Philip, Nisnisan, Josier, Nossuli, A. Kaldun, Obialo, Chamberlain, Olelewe, Sarah, Oliver, Michael, O'Shaughnessy, Andrew, Padron, John, Pankhaniya, Rohit, Parker, Reginald, Patel, Devesh, Patel, Gnyandev, Patel, Nina, Pavon, Humberto, Perez, Armando, Perez, Carlos, Perlman, Alan, Pettis, Karlton, Pharr, Walter, Phillips, Andrea, Purighalla, Raman, Quesada-Suarez, Luis, Ranjan, Rajiv, Rastogi, Sanjeev, Reddy, Jakkidi, Rendell, Marc, Rich, Lisa, Robinson, Michael, Rodriguez, Hector, Rosas, Sylvia, Saba, Fadi, Sankaram, Rallabhandi, Sarin, Ravi, Schreiman, Robert, Scott, David, Sekkarie, Mohamed, Sensenbrenner, John, Shakeel, Muhammad, Shanik, Michael, Shaw, Sylvia, Smith, Stephen, Solomon, Richard, Sprague, Amy, Spry, Leslie, Suchinda, Pusadee, Sultan, Senan, Surampudi, Prasanth, Sussman, Sherry, Tan, Anjanette, Terrelonge, Antonio, Thompson, Michael, Trespalacios, Fernando, Trippe, Bruce, Trueba, Pilar, Twahirwa, Marcel, Updegrove, John, Van Buren, Peter, Vannorsdall, Mark, Varghese, Freemu, Velasquez-Mieyer, Pedro, Ventrapragada, Sailaja, Vukotic, Goga, Wadud, Khurram, Warren, Mark, Watson, Henry, Watts, Ronald, Weiner, Daniel, Welker, James, Welsh, Jean, Williams, Shelley, Zaniewski-Singh, Michelle, Yi, Tae Won, Smyth, Brendan, Di Tanna, Gian Luca, Arnott, Clare, Cardoza, Kathryn, and Kang, Amy

Published
2023
Full Text
View/download PDF

34. A phase I/II study of ARO-HSD, an RNA interference therapeutic, for the treatment of non-alcoholic steatohepatitis

Author

Mak, Lung-Yi, Gane, Ed, Schwabe, Christian, Yoon, Ki Tae, Heo, Jeong, Scott, Russell, Lee, Jeong-Hoon, Lee, Jung Il, Kweon, Young Oh, Weltman, Martin, Harrison, Stephen A., Neuschwander-Tetri, Brent A., Cusi, Kenneth, Loomba, Rohit, Given, Bruce D., Christianson, Dawn R., Garcia-Medel, Eric, Yi, Min, Hamilton, James, and Yuen, Man-Fung

Published
2023
Full Text
View/download PDF

35. Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales

Author

Hoover, David L., Abendroth, Lori J., Browning, Dawn M., Saha, Amartya, Snyder, Keirith, Wagle, Pradeep, Witthaus, Lindsey, Baffaut, Claire, Biederman, Joel A., Bosch, David D., Bracho, Rosvel, Busch, Dennis, Clark, Patrick, Ellsworth, Patrick, Fay, Philip A., Flerchinger, Gerald, Kearney, Sean, Levers, Lucia, Saliendra, Nicanor, Schmer, Marty, Schomberg, Harry, and Scott, Russell L.

Published
2023
Full Text
View/download PDF

37. Community Insights for scoping a NASA Terrestrial Ecology field campaign in drylands: ARID

Author

Feldman, Andrew F., primary, Reed, Sasha, additional, Amaral, Cibele, additional, Babst-Kostecka, Alicja, additional, Babst, Flurin, additional, Biederman, Joel Aaron, additional, Devine, Charles John, additional, Fu, Zheng, additional, Green, Julia K., additional, Guo, Jessica S, additional, Hanan, Niall P, additional, Kokaly, Raymond F, additional, Litvak, Marcy, additional, MacBean, Natasha, additional, Moore, David, additional, Ojima, Dennis, additional, Poulter, Benjamin, additional, Scott, Russell L., additional, Smith, William K., additional, swap, Robert J, additional, Tucker, Compton J., additional, Wang, Lixin, additional, Watts, Jennifer, additional, Wessels, Konrad, additional, Zhang, Fangyue, additional, and Zhang, Wen, additional

Published
2024
Full Text
View/download PDF

39. Digital Research Environment(DRE)-enabled Artificial Intelligence (AI) to facilitate early stage drug development

Author

Jeffrey S. Barrett, Solmaz Eradat Oskoui, Scott Russell, and Amanda Borens

Subjects
artificial intelligence, drug developement, drug discovery, data sharing, digital research environment, Therapeutics. Pharmacology, RM1-950
Abstract

Early-stage drug discovery is highly dependent upon drug target evaluation, understanding of disease progression and identification of patient characteristics linked to disease progression overlaid upon chemical libraries of potential drug candidates. Artificial intelligence (AI) has become a credible approach towards dealing with the diversity and volume of data in the modern drug development phase. There are a growing number of services and solutions available to pharmaceutical sponsors though most prefer to constrain their own data to closed solutions given the intellectual property considerations. Newer platforms offer an alternative, outsourced solution leveraging sponsors data with other, external open-source data to anchor predictions (often proprietary algorithms) which are refined given data indexed upon the sponsor’s own chemical libraries. Digital research environments (DREs) provide a mechanism to ingest, curate, integrate and otherwise manage the diverse data types relevant for drug discovery activities and also provide workspace services from which target sharing and collaboration can occur providing yet another alternative with sponsors being in control of the platform, data and predictive algorithms. Regulatory engagement will be essential in the operationalizing of the various solutions and alternatives; current treatment of drug discovery data may not be adequate with respect to both quality and useability in the future. More sophisticated AI/ML algorithms are likely based on current performance metrics and diverse data types (e.g., imaging and genomic data) will certainly be a more consistent part of the myriad of data types that fuel future AI-based algorithms. This favors a dynamic DRE-enabled environment to support drug discovery.

Published
2023
Full Text
View/download PDF

40. Dissecting mechanisms of granuloma formation in ANCA-associated vasculitis

Author

Henderson, Scott Russell

Subjects
616.6
Abstract

Anti-neutrophil cytoplasm antibodies (ANCA) are associated with a severe form of small vessel systemic vasculitis, in which they target two specific auto-antigens, proteinase-3 (PR3) and myeloperoxidase (MPO) found within neutrophils and monocytes. Granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA) are the main clinical syndromes, both characterized by kidney and lung disease, but granulomatous inflammation is almost exclusively found in GPA, and unlike other manifestations, remains difficult to treat. In GPA patients, PR3 is the predominant ANCA auto-antigen and neutrophil membrane PR3 expression is increased. There has been limited understanding of why granulomata are restricted to this patient subgroup. I have investigated the role of PR3 in driving giant cell and granuloma formation by generating a novel in vitro model. Using extensive tissue culture and microscopy techniques I have been able to demonstrate that PR3 induces both giant cell and granuloma formation in GPA patients’ cells. Giant cells are the precursors to granulomata and I have demonstrated that in GPA patients, monocytes firstly fuse with the persistence of PR3 and then later recruit lymphocytes to form an organized granuloma-like structure. I have developed a unique method of quantifying granuloma formation and I have been able to show that GPA patients show a statistically significant greater rate of PBMC aggregation both spontaneously and in the presence of PR3 compared to MPA patients and healthy controls. I have explored the potential mechanisms of granuloma formation in this patient subgroup. Specifically, IL-6 may be important in driving granuloma formation in GPA patients and supports the notion of PR3-mediated process. PR3 cleaves protease-activated receptor 2 (PAR2) and I have shown that the presence of a PAR2 agonist further augments cell fusion. These findings support the role of PR3-mediated monocyte activation and fusion with additional T cell aggregation. In summary, I have developed a novel system to test giant cell and granuloma formation in GPA patients, a potential platform to evaluate new therapeutic treatments.

Published
2018

42. Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

Author

Wang, Xian, Biederman, Joel A., Knowles, John F., Scott, Russell L., Turner, Alexander J., Dannenberg, Matthew P., Köhler, Philipp, Frankenberg, Christian, Litvak, Marcy E., Flerchinger, Gerald N., Law, Beverly E., Kwon, Hyojung, Reed, Sasha C., Parton, William J., Barron-Gafford, Greg A., and Smith, William K.

Published
2022
Full Text
View/download PDF

43. Scaling Individual Tree Transpiration With Thermal Cameras Reveals Interspecies Differences to Drought Vulnerability.

Author

Javadian, Mostafa, Aubrecht, Donald M., Fisher, Joshua B., Scott, Russell L., Burns, Sean P., Diehl, Jen L., Munger, J. William, and Richardson, Andrew D.

Abstract

Understanding tree transpiration variability is vital for assessing ecosystem water‐use efficiency and forest health amid climate change, yet most landscape‐level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard Forest and Niwot Ridge. PT‐JPL model was used to derive latent heat flux from thermal images at the canopy‐level, showing strong agreement with tower measurements (R2 = 0.70–0.96 at Niwot, 0.59–0.78 at Harvard at half‐hourly to monthly scales) and daily RMSE of 33.5 W/m2 (Niwot) and 52.8 W/m2 (Harvard). Tree‐level analysis revealed species‐specific responses to drought, with lodgepole pine exhibiting greater tolerance than Engelmann spruce at Niwot and red oak showing heightened resistance than red maple at Harvard. These findings show how ecophysiological differences between species result in varying responses to drought and demonstrate that these responses can be characterized by deriving transpiration from crown temperature measurements. Plain Language Summary: Understanding how forests use water, especially during droughts, is crucial for a changing climate. We developed a method using thermal cameras to estimate individual tree water loss (transpiration), something traditional methods lack. These cameras capture temperature data from the tree crown, which is then used to estimate transpiration rates. Tests in two forests showed this method aligns well with existing water use measurements. The study also revealed fascinating differences in how species handle drought. For instance, lodgepole pine outperformed Engelmann spruce in one forest, while red oak proved more resistant than red maple in the other. This shows that the thermal cameras can help assess how different trees resist drought conditions. This thermal camera technique has the potential to become a valuable tool for monitoring forest health as our climate evolves. Key Points: Canopy‐level evapotranspiration derived from thermal cameras agreed well with eddy covariance measurementsCrown temperature measurements facilitated the estimation of individual‐tree transpiration of co‐occurring species using the same approachThe results show interspecific differences in water use and response to drought that align with species traits [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

44. Native myocardial T1 and right ventricular size by CMR predict outcome in systemic sclerosis-associated pulmonary hypertension.

Author

Knight, Daniel S, Virsinskaite, Ruta, Karia, Nina, Cole, Alice R, Maclean, Rory H, Brown, James T, Patel, Rishi K, Razvi, Yousuf, Venneri, Lucia, Kotecha, Tushar, Martinez-Naharro, Ana, Kellman, Peter, Scott-Russell, Ann M, Schreiber, Benjamin E, Ong, Voon H, Denton, Christopher P, Fontana, Marianna, Coghlan, J Gerry, and Muthurangu, Vivek

Subjects
MYOCARDIUM physiology, MORTALITY risk factors, RISK assessment, RESEARCH funding, PULMONARY hypertension, SCIENTIFIC observation, MAGNETIC resonance imaging, RETROSPECTIVE studies, DESCRIPTIVE statistics, MYOCARDIUM, SYSTEMIC scleroderma, RIGHT heart atrium, RIGHT heart ventricle, PULMONARY arterial hypertension, BIOMARKERS, CARDIAC catheterization, PATIENT aftercare, DISEASE complications
Abstract

Objectives Measures of right heart size and function are prognostic in systemic sclerosis-associated pulmonary hypertension (SSc-PH), but the importance of myocardial tissue characterisation remains unclear. We aimed to investigate the predictive potential and interaction of cardiovascular magnetic resonance (CMR) myocardial tissue characterisation and right heart size and function in SSc-PH. Methods A retrospective, single-centre, observational study of 148 SSc-PH patients confirmed by right heart catheterization who underwent clinically indicated CMR including native myocardial T1 and T2 mapping from 2016 to 2023 was performed. Results Sixty-six (45%) patients died during follow-up (median 3.5 years, range 0.1–7.3). Patients who died were older (65 vs 60 years, P  = 0.035) with more dilated (P  < 0.001), hypertrophied (P  = 0.013) and impaired (P  < 0.001) right ventricles, more dilated right atria (P  = 0.043) and higher native myocardial T1 (P  < 0.001). After adjustment for age, indexed right ventricular end-systolic volume (RVESVi, P  = 0.0023) and native T1 (P  = 0.0024) were independent predictors of all-cause mortality. Both RVESVi and native T1 remained independently predictive after adjusting for age and PH subtype (RVESVi P  < 0.001, T1 P  = 0.0056). Optimal prognostic thresholds for RVESVi and native T1 were ≤38 mL/m2 and ≤1119 ms, respectively (P  < 0.001). Patients with RVESVi ≤ 38 mL/m2 and native T1 ≤ 1119 ms had significantly better outcomes than all other combinations (P  < 0.001). Furthermore, patients with RVESVi > 38mL/m2 and native T1 ≤ 1119 ms had significantly better survival than patients with RVESVi > 38mL/m2 and native T1 > 1119ms (P  = 0.017). Conclusion We identified prognostically relevant CMR metrics and thresholds for patients with SSc-PH. Assessing myocardial tissue characterisation alongside right ventricular function confers added value in SSc-PH and may represent an additional treatment target. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

46. Adaptation and Response in Drylands (ARID): Community Insights for Scoping a NASA Terrestrial Ecology Field Campaign in Drylands.

Author

Feldman, Andrew F., Reed, Sasha, Amaral, Cibele, Babst‐Kostecka, Alicja, Babst, Flurin, Biederman, Joel, Devine, Charles, Fu, Zheng, Green, Julia K., Guo, Jessica, Hanan, Niall P., Kokaly, Raymond, Litvak, Marcy, MacBean, Natasha, Moore, David, Ojima, Dennis, Poulter, Benjamin, Scott, Russell L., Smith, William K., and Swap, Robert

Subjects
CLIMATE change, CLIMATE change adaptation, EARTH'S core, SURFACE of the earth, EVIDENCE gaps
Abstract

Dryland ecosystems cover 40% of our planet's land surface, support billions of people, and are responding rapidly to climate and land use change. These expansive systems also dominate core aspects of Earth's climate, storing and exchanging vast amounts of water, carbon, and energy with the atmosphere. Despite their indispensable ecosystem services and high vulnerability to change, drylands are one of the least understood ecosystem types, partly due to challenges studying their heterogeneous landscapes and misconceptions that drylands are unproductive "wastelands." Consequently, inadequate understanding of dryland processes has resulted in poor model representation and forecasting capacity, hindering decision making for these at‐risk ecosystems. NASA satellite resources are increasingly available at the higher resolutions needed to enhance understanding of drylands' heterogeneous spatiotemporal dynamics. NASA's Terrestrial Ecology Program solicited proposals for scoping a multi‐year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. A primary goal of the scoping study is to gather input from the scientific and data end‐user communities on dryland research gaps and data user needs. Here, we provide an overview of the ARID team's community engagement and how it has guided development of our framework. This includes an ARID kickoff meeting with over 300 participants held in October 2023 at the University of Arizona to gather input from data end‐users and scientists. We also summarize insights gained from hundreds of follow‐up activities, including from a tribal‐engagement focused workshop in New Mexico, conference town halls, intensive roundtables, and international engagements. Plain Language Summary: Drylands are landscapes with limited water availability, which cover 40% of Earth's land surfaces, support billions of humans, and play a substantial role in Earth's weather and climate systems. However, these ecosystems are under threat from droughts and heatwaves. They are also poorly understood because of challenges measuring their highly diverse vegetation types and interspersed vegetation cover and because of incorrect perceptions that they are unimportant "wastelands." These limitations make it challenging to manage their landscapes and quantify how drylands are driving Earth's weather and climate. NASA solicited proposals for a multi‐year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. The ARID scoping study aims to design a plan for how NASA satellite, aircraft, and field instruments can be used to better understand dryland ecosystems and their response to change. A primary scoping goal is to engage with scientists and data‐users, especially those who manage land, to understand research and management priorities in drylands. Here, we discuss details of our meeting with over 300 scientists and data‐users in Tucson, AZ in October 2023. We also highlight feedback from our tribal‐focused workshop in New Mexico, conference town halls, and international meetings. Key Points: Adaptation and Response in Drylands (ARID) is a 1‐year scoping study for a multi‐year NASA Terrestrial Ecology dryland field campaignAn ARID workshop was held in Tucson, Arizona in October 2023 with more than 30 data end‐users and 300 scientists in attendanceFurther input from hundreds of researchers and end‐users was obtained through workshops, conference townhalls, and tribal engagement [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

48. Outcomes with Finerenone in Participants with Stage 4 CKD and Type 2 Diabetes: A FIDELITY Subgroup Analysis

Author

Sarafidis, Pantelis, Agarwal, Rajiv, Pitt, Bertram, Wanner, Christoph, Filippatos, Gerasimos, Boletis, John, Tuttle, Katherine R., Ruilope, Luis M., Rossing, Peter, Toto, Robert, Anker, Stefan D., Liu, Zhi-Hong, Joseph, Amer, Ahlers, Christiane, Brinker, Meike, Lawatscheck, Robert, Bakris, George, Aizenberg, Diego, Bartolacci, Inés, Besada, Diego, Bittar, Julio, Chahin, Mariano, Elbert, Alicia, Gelersztein, Elizabeth, Liberman, Alberto, Maffei, Laura, Manghi, Federico Pérez, Sanabria, Hugo, Vallejos, Augusto, Viñes, Gloria, Wassermann, Alfredo, Abhayaratna, Walter, Acharya, Shamasunder, Ekinci, Elif, Lee, Darren, MacIsaac, Richard, Mah, Peak Mann, Nelson, Craig, Packham, David, Pape, Alexia, Roger, Simon, Stephenson, Hugo, Suranyi, Michael, Wittert, Gary, Vale, Elizabeth, Colman, Peter, Colquhoun, David, Ellis, Chris, Joshua, Kim, Pedagogos, Eugenia, Regal, Paul, Topliss, Duncan, Vandeleur, James, Verjans, Johan, Wittert, Gary, Wynne, Katie-Jane, Clodi, Martin, Ebenbichler, Christoph, Fliesser-Görzer, Evelyn, Hanusch, Ursula, Krebs, Michael, Lhotta, Karl, Ludvik, Bernhard, Mayer, Gert, Neudorfer, Peter, Paulweber, Bernhard, Prager, Rudolf, Preiß, Wolfgang, Prischl, Friedrich, Schernthaner, Gerit-Holger, Sourij, Harald, Wiesholzer, Martin, Drexel, Heinz, Oberbauer, Rainer, Schönherr, Hans-Robert, Doubel, Peter, Engelen, Wendy, Gillard, Pieter, Hougardy, Jean-Michel, Krzesinski, Jean-Marie, Maes, Bart, Speeckaert, Marijn, Stas, Koen, van Gaal, Luc, Vanbelleghem, Hilde, Duyck, Francis, Scheen, André, Antunes, Daniela, Botelho, Roberto, Brito, Claudia, Canani, Luis, Canziani, Maria Eugenia, Cerqueira, Maria, de Paula, Rogerio, Eliaschewitz, Freddy, Figueiredo, Carlos Eduardo, Forti, Adriana, Hissa, Miguel, Leite, Emerson Lima Maurilo, Jr, Noronha, Irene, Paolino, Bruno, Paschoalin, Nathalia, Paschoalin, Raphael, Filho, Roberto Pecoits, Pereira, Marcio, Portes, Evandro, Precoma, Dalton, Rea, Rosangela, Riella, Miguel, Salles, Joao Eduardo, Vasconcellos, Eduardo, Vencio, Sergio, Bacci, Marcelo, Maia, Lilia, Villacorta, Aline, Apostolova, Emiliya, Boshnyashka, Radostina, Farah, Ghassan, Georgiev, Dimitar, Gushterova, Valentina, Klyuchkova, Neli, Lucheva, Mariya, Manova, Petya, Minkova, Dotska, Nonchev, Boyan, Pichmanova, Mariyana, Prakova, Zhulieta, Rangelov, Rangel, Rashkov, Rosen, Stanchev, Pavel, Stoyanovska-Elencheva, Bilyana, Tagarev, Zhivko, Temelkova-Kurktschieva, Theodora, Vasileva, Svetla, Yoncheva-Mihaylova, Mariana, Marinchev, Angel, Miteva, Mariya, Barre, Paul, Carlson, Brian, Conway, James, Cournoyer, Serge, Dumas, Richard, Fikry, Sameh, Goluch, Richard, Hamet, Pavel, Hart, Randolph, Henein, Sam, Liutkus, Joanne, Madore, Francois, Martinho, Valdemar, Mazza, Giuseppe, McFarlane, Philip, Keefe, Dennis O′, Peterson, Sean, Schwartz, Daniel, Shu, Daniel, Steele, Andrew, Tellier, Guy, Tennankore, Karthik, Tobe, Sheldon, Tsoukas, George, Tytus, Richard, Vitou, Louise, Walsh, Michael, Weisnagel, Stanley, Wilderman, Igor, Yale, Jean-Francois, El Boreky, Fadia, Kelly, Alan, Leiter, Lawrence, Teitelbaum, Ivor, Cobos, Jorge, Godoy, Juan, González, Fernando, Lobos, Sergio, Palma, Juan Carlos, Prieto Dominguez, Juan Carlos, Reyes, Eliana, Romero, Carmen, Saavedra, Victor, Vega, Mario, Medina, Marcelo, Varleta, Paola, Bu, Ruifang, Cai, Hanqing, Chen, Nan, Chen, Qinkai, Chen, Dejun, Cheng, Jinluo, Dong, Youping, Dong, Junwu, Guan, Tianjun, Hao, Chuanming, Huang, Wen, Jiang, Fangfang, Lei, Minxiang, Li, Ling, Li, Zhonghe, Li, Xuemei, Li, Jingmei, Li, Yan, Liang, Xinling, Liang, Bo, Liu, Fang, Liu, Yinghong, Liu, Yuantao, Liu, Zhihong, Long, Gang, Lu, Guoyuan, Lu, Weiping, Lu, Yibing, Luo, Ping, Ma, Jianhua, Mo, Zhaohui, Niu, Jianying, Peng, Ai, Shen, Jiansong, Shen, Feixia, Shi, Bingyin, Su, Qing, Sun, Zhuxing, Tang, Shuifu, Tong, Nanwei, Wang, Hao, Wang, Xinjun, Wang, Guixia, Wang, Jianqin, Wang, Yangang, Wang, Li, Wei, Jiali, Wu, Tianfeng, Wu, Chaoqing, Xing, Changying, Xiong, Fei, Xu, Xudong, Xu, Ning, Yan, Tiekun, Yang, Jinkui, Yin, Aiping, Zeng, Longyi, Zhang, Hao, Zhang, Yanlin, Zhang, Ying, Zhao, Wenjing, Zhao, Zhiquan, Zheng, Hongguang, Zhong, Ling, Zhu, Dalong, Zhuang, Yongze, Du, Yuming, Fang, Yi, Guo, Weiying, Jiang, Sheng, Kuang, Jian, Li, Dongmei, Li, Hongmei, Li, Yinan, Li, Yuxiu, Liu, Jian, Liu, Yu, Miao, Heng, Peng, Wen, Wang, Lihua, Xu, Mingtong, Zhong, Liyong, Zhu, Jun, Arango, Clara, Barrera, Sandra, López, Nelly Beltrán, Benitez, Diego, Blanco, Guillermo, Cadena, Andrés, Coronel, Julian, Cure, Carlos, Durán, Carlos, González, Alexander, Guzmán, Gustavo, Hernández, Eric, Ibarra, Jaime, Jaramillo, Carlos, Jaramillo, Nicolás, Kattah, William, Molina, Dora, Sánchez, Gregorio, Terront, Mónica, Trujillo, Freddy, Urina, Miguel, Vargas, Ruben, Villegas, Iván, Yupanqui, Hernán, Arcos, Edgar, Aroca, Gustavo, Barreto, Germán, Bermudez, Andres, Botero, Rodrigo, Cárdenas, Tatiana, Figueroa, Wilmer, Jaramillo, Mónica, Liévano, Manuel, López, Mónica, Molina, Dora, Rosero, Ricardo, Trillos, Pedro, Dino Alferi, Brada, Michal, Brezina, Jiri, Bucek, Petr, Edelsberger, Tomas, Gulakova, Drahomira, Zapletalova, Jitka Hasalova, Hola, Olga, Hornova, Lucie, Houdova, Jana, Hrmova, Helena, Karasek, David, Kopecka, Sarka, Kovar, Richard, Krcova, Eva, Kuchar, Jiri, Kutejova, Vlasta, Lubanda, Hana, Matyasek, Ivo, Mokrejsova, Magdalena, Okenka, Libor, Prazny, Martin, Pumprla, Jiri, Tomanek, Pavel, Andersen, Ulla, Andries, Alin, Bech, Jesper, Faber, Jens, Gislason, Gunnar, Hangaard, Jørgen, Pacyk, Grzegorz Jaroslaw, Juhl, Claus, Krarup, Thure, Lindhardt, Morten, Madsbad, Sten, Nielsen, Joan, Pedersen-Bjergaard, Ulrik, Poulsen, Per, Rasmussen, Ole, Rossing, Peter, Schousboe, Karoline, Gram, Jeppe, Lauridsen, Thomas, Pedersen, Erling, Thorsteinsson, Birger, Flöjt, Päivi, Honkasalo, Mikko, Honkasalo, Mikko, Humaloja, Kari, Kananen, Kristiina, Kantola, Ilkka, Koistinen, Arvo, Korsoff, Pirkko, Lahtela, Jorma, Nieminen, Sakari, Nieminen, Tuomo, Sadeharju, Karita, Strand, Jorma, Sulosaari, Sakari, Cariou, Bertrand, Chantrel, François, Clavel, Sylvaine, Combe, Christian, Fauvel, Jean-Pierre, Gallouj, Karim, Gouet, Didier, Guerci, Bruno, Guerrot, Dominique, Hourmant, Maryvonne, Klein, Alexandre, Mariat, Christophe, Marre, Michel, Mesbah, Rafik, Le Meur, Yannick, Monier, Arnaud, Moranne, Olivier, Roussel, Ronan, Serusclat, Pierre, Vendrely, Benoit, Verges, Bruno, Zaoui, Philippe, Axthelm, Christoph, Bergmann, Andreas, Birkenfeld, Andreas L., Braun, Hermann, Busch, Klaus, Contzen, Christel, Degenhardt, Stefan, Derwahl, Karl, Giebel, Thomas, Hagenow, Andreas, Haller, Hermann, Hasslacher, Christoph, Horacek, Thomas, Jungmair, Wolfgang, Kloos, Christof, Koch, Thorsten, Krüger, Thilo, Mühlfeld, Anja, Müller, Joachim, Pfützner, Andreas, Pistrosch, Frank, Rinke, Andrea, Rose, Ludger, Rump, Lars, Schettler, Volker, Schiefke, Ingolf, Schlichthaar, Heike, Schröppel, Bernd, Schöll, Norbert, Schubert, Kristin, Schürholz, Thomas, Sigal, Helena, Stemler, Lutz, Strack, Georg, Täschner, Heidrun, Toursarkissian, Nicole, Tschöpe, Diethelm, Ulmer, Achim, van der Giet, Markus, Wanner, Christoph, Winkelmann, Bernhard R., Boletis, Ioannis, Dimitriadis, George, Hatziagelaki, Erifili, Iatrou, Christos, Ioannidis, Ioannis, Kounadi, Theodora, Makriniotou, Ioanna, Papadopoulou, Dorothea, Papagianni, Aikaterini, Passadakis, Ploumis, Piaditis, George, Stefanidis, Ioannis, Tai Pang Ip, Lee, Paul, Andrea Luk, On Yan, Ma, Ronald, Chow, Wing Sun, Wang, Angela, Yeung, Vincent, Bajcsi, Dora, Danos, Peter, Harcsa, Eleonora, Kalina, Akos, Kazup, Szilvia, Keltai, Katalin, Kirschner, Robert, Kiss, Julianna, Kovacs, Laszlo, Lamboy, Beata, Literati-Nagy, Botond, Mileder, Margit, Nagy, Laszlo, Noori, Ebrahim, Nyirati, Gabor, Petro, Gizella, Schneider, Karoly, Simon, Judit, Szocs, Albert, Vasas, Szilard, Wudi, Krisztina, Zilahi, Zsolt, Zsom, Marianna, Eustace, Joe, Holian, John, Reddan, Donal, Meara, Yvonne O′, Abramof Ness, Rosane, Adawi, Faiad, Armaly, Zaher, Atar, Shaul, Bashkin, Amir, Ben Chetrit, Sydney, Yanay, Noa Berar, Chernin, Gil, Darawsha, Mahmud, Efrati, Shai, Elias, Mazen, Farber, Evgeny, Glandt, Mariela, Grossman, Ehud, Halabi, Majdi, Harman-Boehm, Ilana, Khazim, Khaled, Liberty, Idit, Minuchin, Oscar, Mosenzon, Ofri, Nakhoul, Farid, Nimer, Assy, Schwartz, Doron, Wainstein, Julio, Yagil, Yoram, Zukermann, Robert, Avogaro, Angelo, Battaglia, Giovanni Giorgio, Bevilacqua, Maurizio Tiziano, Bonora, Enzo, Bossi, Carlo Antonio, Calabrò, Paolo, Cavalot, Franco Luigi, Cimino, Roberto, Cozzolino, Mario Gennaro, David, Salvatore, Emdin, Michele, Fiaccadori, Enrico, Fiorina, Paolo, Giorda, Carlo Bruno, Gregorini, Maria Cristina, La Manna, Gaetano, Maggi, Davide Carlo, Manti, Roberta, Meregalli, Giancarla, Pani, Antonello, Parvanova, Aneliy Ilieva, Perico, Norberto, Piatti, PierMarco, Pisani, Antonio, Pontiroli, Antonio Ettore, Ponzani, Paola, Santorelli, Gennaro, Santoro, Domenico, Scanziani, Renzo, Teatini, Ugo, Tonolo, Giancarlo, Trevisan, Roberto, Veronelli, Anna Maria, Viviani, Giorgio Luciano, Araki, Hideo, Bando, Yukihiro, Ebisui, Osamu, Fujita, Naruhiro, Fukasawa, Hirotaka, Furuya, Ryuichi, Hamamoto, Yoshiyuki, Hamasaki, Akihiro, Hasegawa, Kotaro, Hatazaki, Masahiro, Hayashi, Terumasa, Higashi, Takayuki, Hirohata, Yoshihide, Horinouchi, Shuji, Hoshi, Ayumu, Imoto, Hirofumi, Inagaki, Akemi, Inagaki, Masayuki, Inaguma, Daijo, Inoue, Toshihiko, Ishii, Masao, Ishiko, Tamayo, Isono, Motohide, Jinnouchi, Hideaki, Kanai, Hidetoshi, Kanda, Daisuke, Kanehara, Hideo, Kashima, Masayuki, Kataoka, Yuko, Katayama, Shigehiro, Kato, Kiyoe, Katsuki, Takeshi, Kawamitsu, Katsunori, Kawasaki, Satsuki, Kikuchi, Fumi, Kikuchi, Hidetoshi, Kishimoto, Rui, Kobayashi, Kunihisa, Koide, Junko, Komi, Rieko, Kubota, Miyuki, Kuriya, Genpei, Kurose, Takeshi, Kusano, Yoshiro, Hajime, Maeda, Matsubayashi, Sunao, Matsumoto, Kazunari, Matsumura, Naoya, Matsuo, Yasuto, Matsuoka, Naoki, Miyaoka, Hiroaki, Miyata, Satoshi, Morita, Takeshi, Murakami, Isao, Murao, Satoshi, Nakamura, Udai, Nakayama, Mikihiro, Nakazawa, Jun, Nohara, Sakae, Nomiyama, Takashi, Noritake, Masayuki, Oda, Yoshiaki, Ogiwara, Takayuki, Ohashi, Hiroshi, Okamoto, Hideki, Okino, Shinichi, Osonoi, Takeshi, Sasaki, Nobuhiro, Sayo, Yoshitaka, Sekigami, Taiji, Shibasaki, Taro, Shibata, Hirotaka, Shimoyama, Tatsushi, Shinoda, Junji, Sobajima, Hiroshi, Sugitatsu, Kazuya, Sugiura, Toshiyuki, Sugiyama, Toru, Suzuki, Daisuke, Suzuki, Hiroyuki, Suzuki, Masaaki, Takeda, Asami, Tanaka, Asami, Tanaka, Seiichi, Tsunematsu, Izumi, Ueda, Yasuo, Uekihara, Soichi, Ujihara, Makoto, Yajima, Ken, Yamada, Daishiro, Yamada, Masayo, Yamagata, Kazuo, Yamakawa, Ken, Yamakawa, Fumiko, Yamasaki, Yoshimitsu, Yambe, Yuko, Yanagida, Taihei, Yanai, Hidekatsu, Yanase, Toshihiko, Yasuda, Tetsuyuki, Kriauciuniene, Dovile, Lasiene, Jurate, Navickas, Antanas, Radzeviciene, Lina, Urbanaviciene, Egle, Urbonas, Gediminas, Velaviciene, Audrone, Abd Ghani, Rohana, Aziz, Nor Azizah, Lee, Li Yuan, Loh, Chek Loong, Ali, Norhaliza Mohd, Noor, Nurain Mohd, Fatnoon Nik Ahmad, Nik Nur, Ratnasingam, Jeyakantha, Halimi Bin Wan Hasan, Wan Hasnul, Izani Wan Mohamed, Wan Mohd, Khir, Rizmy Najme, Mohamad, Masni, Alexander Tan, Tong Boon, Avila Pardo, Sandro, Adrian, Miriam Bastidas, Wong, Alfredo Chew, Escobedo de la Peña, Jorge, Salmón, Guillermo Fanghänel, Gálvez, Guillermo González, Ochoa, Ramiro Gutiérrez, Santana, Saúl Irizar, Rovalo, Magdalena Madero, Machado, Gustavo Méndez, Ruiz, Luis Nevarez, Ibarra, Denisse Ramos, López, Gabriel Ramos, Reyna, Leobardo Sauque, Ortiz, Gustavo Solache, Ortiz, Rafael Valdez, Mesa, Juan Villagordoa, Salazar, Melchor Alpizar, Hernández, Pedro García, González, José, Soto, José Lazcano, Mendoza, Arturo Saldaña, Santana, Sergio Irizar, Vilchis, Elvira González, Bakker, R.C., Barendregt, J.N.M., Boonstra, A.H., Bos, Willem, Brouwer, C.B., Buren, M. van, Gansevoort, Ron, Kooy, Adriaan, Krekels, Marielle, Leendert, Ruud J.M. van, Lieverse, Louis A.G., Luik, P.T., Penne, E. Lars, Gregoor, Peter Smak, Vogt, Liffert, Born, Bert-Jan van den, John Baker, Crawford, Veronica, Cutfield, Rick, Dunn, Peter, Krebs, Jeremy, Nirmalaraj, Kingsley, Scott, Russell, Smuts, Nine, Titchener, Janet, Eriksen, Erik, Finnes, Trine, Høivik, Hans, Karlsson, Thomas, Munk, Peter Scott, Radtke, Maria, Risberg, Knut, Rocke, Jan, Solnør, Leidulv, Stenehjem, Aud-Eldrid, Tafjord, Anne-Beathe, Asprusten, Emil, Hagemeier, Robert, Høye, Kjetil, Selsås, Hilde, Thorup, Frode, Wium, Cecilie, Pamugas, Glenda, Panelo, Araceli, Perez, Ronald, Tanque, Maribel, Tirador, Louie, Villa, Michael, Bautista, Albert, Catindig, Elizabeth, Manalo, Carlo, Mirasol, Roberto, Butrymowicz, Patrycja, Ciechanowski, Kazimierz, Cieslik, Grazyna, Franek, Edward, Gumprecht, Janusz, Hoffmann, Michal, Krzykowska, Jolanta, Kurnatowska, Ilona, Landa, Katarzyna, Madrzejewski, Adam, Madziarska, Katarzyna, Mazur, Stanislaw, Napora, Piotr, Nowicki, Michal, Ocicka-Kozakiewicz, Anna, Rewerska, Barbara, Rusicka, Teresa, Ruxer, Jan, Skokowska, Ewa, Stankiewicz, Andrzej, Stompor, Tomasz, Tiuryn-Petrulewicz, Agnieszka, Wasilewska, Katarzyna, Wierusz-Wysocka, Bogna, Wnetrzak-Michalska, Renata, Jedynasty, Krystyna, Anand, Izabela Sein, Almeida, Edgar, Ballesteros, Rosa, Barreto, Carlos, Beirao, Idalina, Birne, Rita, Esteves, Cesar, Guia, Jose, Heitor, Susana, Marques, Olinda, Melo, Pedro, Nolasco, Fernando, Pereira, Amalia, Roque, Cristina, Rosario, Francisco, Silva, Gil, Silva, Ana, Teixeira e Costa, Fernando, Lobos, Ana Vila, Alves, Ana Rita, Brandao, Ilidio, Carvalho, Rui, Coelho, Joao, Lourenco, Ana, Matos, Pedro, Rosario, Vanisa, Neves, Joao Sergio, Cortes-Maisonet, Gregorio, Roman-Miranda, Amaury, Brito-Peguero, Yudit, Colon-Vega, Gildred, Albota, Adrian, Bala, Cornelia, Barbonta, Hortensia, Caceaune, Elena, Catrinoui, Doina, Constantin, Ciprian, Dumitrescu, Adriana, Mindrescu, Nicoleta, Mistode, Cristina, Negrisanu, Gabriela, Onaca, Adriana, Paveliu, Silvia, Pintilei, Ella, Pop, Lavinia, Popa, Amorin, Popescu, Alexandrina, Radulian, Gabriela, Szilagyi, Iosif, Turcu, Liana, Vacaru, Georgeta, Vlad, Adrian, Filimon, Adriana, Veresiu, Ioan, Antsiferov, Mikhail, Arkhipov, Mikhail, Babkin, Andrey, Barbarash, Olga, Baranov, Vitaliy, Chernyavskaya, Elena, Demko, Arkadiy, Dreval, Alexander, Edin, Anton, Ermakova, Polina, Fadeev, Valentin, Galyavich, Albert, Gaysina, Leyla, Gordeev, Ivan, Ipatko, Irina, Kalashnikova, Marina, Khalimov, Yuriy, Klimontov, Vadim, Kobalava, Zhanna, Kosmacheva, Elena, Koziolova, Natalya, Sergey Levashov, Lyudmila Kvitkova, Libis, Roman, Marasaev, Vyacheslav, Malykh, Natalia, Martynenko, Vladimir, Malyutina, Sofya, Merai, Imad, Mkrtumyan, Ashot, Nechaeva, Galina, Petunina, Nina, Palyutin, Shamil, Pimenov, Leonid, Rechkova, Elena, Rodionova, Tatyana, Rymar, Oksana, Sardinov, Ruslan, Semenova, Olga, Sherenkov, Alexander, Solovev, Oleg, Smolyarchuk, Elena, Strongin, Leonid, Ukhanova, Olga, Verlan, Nadezhda, Vorokhobina, Natalya, Yakhontov, Davyd, Yakushin, Sergey, Zakharova, Elena, Zalevskaya, Alsu, Zanozina, Olga, Zhdanova, Elena, Zhukova, Larisa, Zykova, Tatyana, Argunova, Yulia, Nikolaev, Konstantin, Villevalde, Svetlana, Fang Sum, Chee, Suhail, Sufi Muhummad, San Tan, Ru, Vathsala, Anantharaman, Wong, Edmund, Bee, Yong Mong, Babikova, Jana, Buganova, Ingrid, Dzupina, Andrej, Ochodnicka, Zuzana, Sosovec, Dalibor, Spodniakova, Denisa, Minarik, Peter, Fayzal Ahmed, Amod, Aslam, Bhana, Sindeep, Distiller, Larry, Jansen van Rensburg, Dirkie, Joshi, Mukesh, Joshi, Shaifali, Lakha, Deepak, Mitha, Essack, Podgorski, Gracjan, Ranjith, Naresh, Rayner, Brian, Rheeder, Paul, Sarvan, Mohamed, Seeber, Mary, Siebert, Heidi, Tayob, Mohammed, Trokis, Julien, Urbach, Dorothea, van Zyl, Louis, Jansen van Rensburg, Dirkie, Bum-Soon Choi, Choi, Moon Gi, Chung, ChoonHee, Hwang, YouCheol, Kim, ChongHwa, Kim, InJoo, Kim, JaeHyeon, Kim, SinGon, Kim, SungGyun, Kim, Tae Hee, Lee, WooJe, Lee, ByungWan, Lee, Kang Wook, Oh, Kook-Hwan, Oh, Ji Eun, Oh, Yun Kyu, Oh, Dong-Jin, Park, Junbeom, Shin, Seok Joon, Sung, Su-Ah, Yu, Jae Myung, Chung, HyeSoo, Huh, Ji Hye, Kang, JunGoo, Kim, ChulSik, Kim, HyeSoon, Kim, NamHoon, Lim, Soo, Cho, Young Min, Park, Cheol Young, Agraz, Irene, Ampudia, Francisco Javier, Bouarich, Hanane, Calero, Francesca, Castro, Cristina, Guldris, Secundino Cigarrán, Garrit, Josep Cruzado, de Álvaro, Fernando, Galcerán, Josep, Albarrán, Olga González, Jaras, Julio Hernández, Ibernón, Meritxell, Deben, Francisco Martínez, Ma, Esteban, Dolores Martínez, Pascual Izuel, José María, Martins, Judith, Mediavilla, Juan, Michán, Alfredo, Santos, Julio Pascual, Poch, Esteban, Rusillo, Manuel Polaina, Juan, Carlos Sánchez, Olmo, Rafael Santamaría, Segura de la Morena, José Julián, Soto, Alfonso, Troya, Maribel, Castro, Fernando Cereto, Fernández, Pablo Gómez, Sánchez, Laura Fuentes, Moya, Mercedes González, Marrero, Domingo Hernández, Maroto, Gonzalo Piedrola, Redón, Josep, Seron, Daniel, Bruchfeld, Annette, Curiac, Dan, Eliasson, Ken, Frank, Malin, Guron, Gregor, Hellberg, Olof, Hellgren, Margareta, Larnefeldt, Hans, Lindholm, Carl-Johan, Löndahl, Magnus, Rein-Hedin, Erik, Soveri, Inga, Spaak, Jonas, Tengmark, Bengt-Olov, Lif-Tiberg, Cornelia, Månflod, Johan, Nguyen, Han, Ackermann, Daniel, Bilz, Stefan, Burnier, Michel, Forster, Christian, Kalbermatter, Stefan, Kistler, Andreas, Pechère-Bertschi, Antoinette, Schultes, Bernd, Laimer, Markus, Rudofsky, Gottfried, Strey, Christopher, Wuerzner, Gregoire, Chiz-Tzung Chang, Hung, Cheng-Chieh, Jiang, Ju-Ying, Lee, Chien-Te, Lin, Shuei-Liong, Tarng, Der-Cherng, Tu, Shih-Te, Wu, Mai-Szu, Wu, Ming-Ju, Chuang, Lee-Ming, Deerochanawong, Chaicharn, Kitiyakara, Chagriya, Ophascharoensuk, Vuddhidej, Pongchaiyakul, Chatlert, Satirapoj, Bancha, Kosachunhanan, Natapong, Sritara, Piyamitr, Eren, Necmi, Gul, Ibrahim, Gulel, Okan, Kocyigit, Ismail, Kumbasar, Abdulbaki, Sahin, Idris, Sari, Ramazan, Sayin, Burak, Tavli, Talat, Ustundag, Sedat, Yenicerioglu, Yavuz, Badak, Ozer, Cayli, Murat, Oguz, Aytekin, Ozdogan, Oner, Sari, Ibrahim, Temizhan, Ahmet, Tigen, Mustafa, Turk, Ugur, Yilmaz, Huseyin, Yilmaz, Mehmet, Bondarets, Iryna, Botsyurko, Volodymyr, Chernikova, Viktoriia, Donets, Oleksandra, Fushtey, Ivan, Grachova, Mariia, Isayeva, Anna, Kogut, Dmytro, Komisarenko, Julia, Kravchun, Nonna, Malyar, Kateryna, Mankovsky, Borys, Martynyuk, Liliya, Maslyanko, Vitaliy, Myshanych, Halyna, Pererva, Larysa, Pertseva, Nataliia, Serhiyenko, Oleksandr, Smirnov, Ivan, Sokolova, Liubov, Stryzhak, Vasyl, Vlasenko, Maryna, Isayeva, Ganna, Larin, Oleksandr, Ahmad AbouSaleh, Barratt, Jonathan, Dang, Cuong, Kahal, Hassan, Kirk, Adam, Kilvert, Anne, Kon, Sui Phi, McCafferty, Kieran, Patel, Dipesh, Rice, Sam, Vijayaraman, Arutchelvam, Wong, Yuk-ki, Gibson, Martin, Wahba, Mona, Zaidi, Reza, Bilous, Rudy, Johnson, Andrew, Kalathil, Dhanya, Kilvert, Anne, Kyriakidou, Christina, Mathew, Amit, Mukhtar, Rasha, Munsoor, Imrozia, Poterajlo, Anton, Swift, Pauline, Idalia Acosta, Adams, Atoya, Adler, Sharon, Ajani, Dilawar, Ali, Slamat, Alicic, Radica, Al-Karadsheh, Amer, Alla, Sreedhara, Allison, D., Andrawis, Nabil, Arif, Ahmed, Awad, Ahmed, Azizad, Masoud, Bahrami, Michael, Bansal, Shweta, Barag, Steven, Barakzoy, Ahmad, Barney, Mark, Barzilay, Joshua, Bashir, Khalid, Bautista, Jose, Beddhu, Srinivasan, Belo, Diogo, Benjamin, Sabrina, Berenji, Ramin, Bhargava, Anuj, Birriel, Jose, Brietzke, Stephen, Brosius, Frank, Brusco, Osvaldo, Burgner, Anna, Busch, Robert, Canadas, Rafael, Caramori, Maria, Cardona, Jose, Case, Christopher, Cruz, Humberto, Dandillaya, Ramprasad, Dawoud, Dalia, Din, Zia, Dixon, Bradley, Doshi, Ankur, Drakakis, James, El Shahawy, Mahfouz, El-Meanawy, Ashraf, El-Shahawy, Mohammed, Evans, John, Fadda, George, Farooq, Umar, Fernando, Roland, Fink, Raymond, First, Brian, Fitz-Patrick, David, Flack, John, Fluck, Patrick, Fogelfeld, Leon, Fonseca, Vivian, Frias, Juan, Galphin, Claude, Garcia-Mayol, Luis, Goldstein, Gary, Gonzalez, Edgar, Gonzalez-Abreu, Francisco, Gore, Ashwini, Grant, David, Habwe, Violet, Hamilton, Maxine, Hammoud, Jamal, Handelsman, Stuart, Hartman, Israel, Heigerick, Glenn, Henry, Andrew, Hernandez, German, Hernandez-Cassis, Carlos, Herrera, Carlos, Hertel, Joachim, Huang, Wenyu, Iglesias, Rogelio, Iranmanesh, Ali, Jackson, Timothy, Jain, Mahendra, Jamerson, Kenneth, Johnson, Karen, Judd, Eric, Kaplan, Joshua, Kayali, Zeid, Khan, Bobby, Khan, Muhammad, Kharait, Sourabh, Kirkman, M. Sue, Kopyt, Nelson, Kotzker, Wayne, Kovesdy, Csaba, Kreit, Camil, Krishna, Arvind, Kronfli, Saeed, Lee, Keung, LeJeune, Derek, Lemus, Brenda, Leon-Forero, Carlos, Linfert, Douglas, Lora, Henry, Lurie, Alexander, Maddukuri, Geetha, Magno, Alexander, Maletz, Louis, Mandayam, Sreedhar, Markell, Mariana, Mayfield, Ronald, Mbogua, Caroline, McMullen, Dierdre, Meisner, Carl, Minton, Stephen, Mocherla, Bharat, Mohandas, Rajesh, Montero, Manuel, Moustafa, Moustafa, Nadkarni, Salil, Nakhle, Samer, Navarro, Jesus, Neyra, Nilda, Nica, Romanita, Nicol, Philip, Norwood, Paul, Numrungroad, Visal, Donovan, Richard O′, Odugbesan, A., Paoli-Bruno, Jorge, Parikh, Samir, Patel, Rakesh, Peixoto, Aldo, Pergola, Pablo, Perlman, Alan, Pettis, Karlton, Pisoni, Roberto, Ponduchi, Mirela, Posada, Jorge, Prabhakar, Sharma, Radhakrishnan, Jai, Rahman, Mahboob, Raina, Rupesh, Rastogi, Anjay, Reisin, Efrain, Rendell, Marc, Robertson, David, Rocco, Michael, Romeu, Hugo, Rosas, Sylvia, Rosenfeld, Jack, Ross, Dennis, Rothman, Jeffrey, Rudolph, Lance, Ruhullah, Yusuf, Ruoff, Gary, Ryu, Jeffrey, Sahani, Mandeep, Sam, Ramin, Samuels, Garfield, Sanchez, William, Santos, Vladimir, Satko, Scott, Saxena, Sanjeev, Scott, David, Seco, Gilberto, Seek, Melvin, Serota, Harvey, Shafi, Tariq, Shahid, Nauman, Shanik, Michael, Sharma, Santosh, Sinha, Arjun, Smelser, James, Smith, Mark, Soe, Kyaw, Solomon, Richard, Soroka, Eugene, Soufer, Joseph, Spinowitz, Bruce, Spry, Leslie, Suarez, Rosa, Subramanian, Bala, Szerlip, Harold, Tamirisa, Aparna, Thomson, Stephen, Tran, Tuan-Huy, Treger, Richard, Trullenque, Gretel, Turk, Thomas, Umpierrez, Guillermo, Urbach, Daniel, Valdes, Martin, Valika, Shujauddin, Vega, Damaris, Weissman, Peter, Whaley-Connell, Adam, Winston, Jonathan, Wise, Jonathan, Wynne, Alan, Zeig, Steven, Abdel-Rahman, Emaad, Abreu, Edel, Awad, Alaa, Bahri, Nader, Bertsch, John, Bleich, David, Bornfreund, Jonathan, Brar, Harjeet, Brian, Susan, Brinson, Cynthia, Bruschetta, Humberto, Carpio, Jose, Cohen, Steven, Cosby, John, Dhanireddy, Soni, Diaz, Jorge, Dunn, Fredrick, Eppanapally, Sabitha, Fayad, Joseph, Goel, Archana, Govindaraju, Kanakadurga, Halpern, Stephen, Jones, Audrey, Kaye, William, Knight, Herbert, Koch, Stanley, Kohli, Nandini, Lastra, Guido, Lerman, Sam, Loredo, Jorge, Lovre, Dragana, Mandviwala, Mustafa, Martin, Earl, Meyer, Jill, Murray, John, Oliver, David, Oparil, Suzanne, Penabad, Jesus, Pereira, Isabel, Popeil, Larry, Quesada, Gonzalo, Ramanathan, Kodangudi, Ramos-Gonez, Luis, Rastegar, Mandana, Rastogi, Padmashri, Rondon, Juan, Roy-Chaudhury, Prabir, Smith, David, Williamson, Don, Womack, Catherine, Yamout, Hala, Yuryev, Michael, Chu, Phuong, Van Hoang, Lam, Khanh, Tran, Phi Nga, Nguyen Thi, Son, Pham Nguyen, Tran, Lan Phuong, Le, Thuy Khuong, Nguyen, Boi Ngoc, Nguyen, Thao, Nui, Nguyen Minh, Nam, Tran Quang, and Tran, Kim Chi

Published
2023
Full Text
View/download PDF

49. Coupling Remote Sensing with a Process Model for the Simulation of Rangeland Carbon Dynamics

Author

Xia, Yushu, primary, Sanderman, Jonathan, additional, Watts, Jennifer, additional, Machmuller, Megan B, additional, Mullen, Andrew L., additional, Rivard, Charlotte, additional, Endsley, K. Arthur, additional, Hernandez, Haydee, additional, Kimball, John, additional, Ewing, Stephanie A, additional, Litvak, Marcy, additional, Duman, Tomer, additional, Krishnan, Praveena, additional, Meyers, Tilden, additional, Brunsell, Nathaniel A, additional, Mohanty, Binayak, additional, Liu, Heping, additional, Gao, Zhongming, additional, Chen, Jiquan, additional, Abraha, Michael, additional, Scott, Russell L., additional, Flerchinger, Gerald, additional, Clark, Pat, additional, Stoy, Paul Christopher, additional, Khan, Anam Munir, additional, Brookshire, Jack, additional, Zhang, Quan, additional, Cook, David R, additional, Thienelt, Thomas, additional, Mitra, Bhaskar, additional, Mauritz, Marguerite, additional, Tweedie, Craig, additional, Torn, Margaret S., additional, and Billesbach, Dave, additional

Published
2024
Full Text
View/download PDF

50. Albedo‐Induced Global Warming Potential Following Disturbances in Global Temperate and Boreal Forests

Author

Zhu, Qingsong, primary, Chen, Jiquan, additional, Charles P.‐A., Bourque, additional, Sonnentag, Oliver, additional, Montagnani, Leonardo, additional, O’Halloran, Thomas L., additional, Scott, Russell L., additional, Forsythe, Jeremy, additional, Song, Bo, additional, Zou, Huimin, additional, Duan, Meihui, additional, and Li, Xianglan, additional

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results